Juliette Hayer

HBVdb: a knowledge database for Hepatitis B Virus

We have developed a specialized database, HBVdb (http://hbvdb.ibcp.fr), allowing the researchers to investigate the genetic variability of Hepatitis B Virus (HBV) and viral resistance to treatment. HBV is a major health problem worldwide with more than 350 million individuals being chronically infected. HBV is an enveloped DNA virus that replicates by reverse transcription of an RNA intermediate. HBV genome is optimized, being circular and encoding four overlapping reading frames. Indeed, each nucleotide of the genome takes part in the coding of at least one protein. However, HBV shows some genome variability leading to at least eight different genotypes and recombinant forms. The main drugs used to treat infected patients are nucleos(t)ides analogs (reverse transcriptase inhibitors). Unfortunately, HBV mutants resistant to these drugs may be selected and be responsible for treatment failure. HBVdb contains a collection of computer-annotated sequences based on manually annotated reference genomes. The database can be accessed through a web interface that allows static and dynamic queries and offers integrated generic sequence analysis tools and specialized analysis tools (e.g. annotation, genotyping, drug resistance profiling).

The Bee Microbiome: Impact on Bee Health and Model for Evolution and Ecology of Host-Microbe Interactions

ABSTRACT As pollinators, bees are cornerstones for terrestrial ecosystem stability and key components in agricultural productivity. All animals, including bees, are associated with a diverse community of microbes, commonly referred to as the microbiome. The bee microbiome is likely to be a crucial factor affecting host health. However, with the exception of a few pathogens, the impacts of most members of the bee microbiome on host health are poorly understood. Further, the evolutionary and ecological forces that shape and change the microbiome are unclear. Here, we discuss recent progress in our understanding of the bee microbiome, and we present challenges associated with its investigation. We conclude that global coordination of research efforts is needed to fully understand the complex and highly dynamic nature of the interplay between the bee microbiome, its host, and the environment. High-throughput sequencing technologies are ideal for exploring complex biological systems, including host-microbe interactions. To maximize their value and to improve assessment of the factors affecting bee health, sequence data should be archived, curated, and analyzed in ways that promote the synthesis of different studies. To this end, the BeeBiome consortium aims to develop an online database which would provide reference sequences, archive metadata, and host analytical resources. The goal would be to support applied and fundamental research on bees and their associated microbes and to provide a collaborative framework for sharing primary data from different research programs, thus furthering our understanding of the bee microbiome and its impact on pollinator health.

Discovery of Novel Viruses in Mosquitoes from the Zambezi Valley of Mozambique

Mosquitoes carry a wide variety of viruses that can cause vector-borne infectious diseases and affect both human and veterinary public health. Although Mozambique can be considered a hot spot for emerging infectious diseases due to factors such as a rich vector population and a close vector/human/wildlife interface, the viral flora in mosquitoes have not previously been investigated. In this study, viral metagenomics was employed to analyze the viral communities in Culex and Mansonia mosquitoes in the Zambezia province of Mozambique. Among the 1.7 and 2.6 million sequences produced from the Culex and Mansonia samples, respectively, 3269 and 983 reads were classified as viral sequences. Viruses belonging to the Flaviviridae, Rhabdoviridae and Iflaviridae families were detected, and different unclassified single- and double-stranded RNA viruses were also identified. A near complete genome of a flavivirus, tentatively named Cuacua virus, was obtained from the Mansonia mosquitoes. Phylogenetic analysis of this flavivirus, using the NS5 amino acid sequence, showed that it grouped with ‘insect-specific’ viruses and was most closely related to Nakiwogo virus previously identified in Uganda. Both mosquito genera had viral sequences related to Rhabdoviruses, and these were most closely related to Culex tritaeniorhynchus rhabdovirus (CTRV). The results from this study suggest that several viruses specific for insects belonging to, for example, the Flaviviridae and Rhabdoviridae families, as well as a number of unclassified RNA viruses, are present in mosquitoes in Mozambique.

The Intestinal Eukaryotic Virome in Healthy and Diarrhoeic Neonatal Piglets

Neonatal porcine diarrhoea of uncertain aetiology has been reported from a number of European countries. The aim of the present study was to use viral metagenomics to examine a potential viral involvement in this diarrhoea and to describe the intestinal virome with focus on eukaryotic viruses. Samples from the distal jejunum of 50 diarrhoeic and 19 healthy piglets from 10 affected herds were analysed. The viral fraction of the samples was isolated and nucleic acids (RNA and DNA fractions) were subjected to sequence independent amplification. Samples from diarrhoeic piglets from the same herds were pooled whereas samples from healthy piglets were analysed individually. In total, 29 clinical samples, plus two negative controls and one positive control consisting of a mock metagenome were sequenced using the Ion Torrent platform. The resulting sequence data was subjected to taxonomic classification using Kraken, Diamond and HMMER. In the healthy specimens, eight different mammalian virus families were detected (Adenoviridae, Anelloviridae, Astroviridae, Caliciviridae, Circoviridae, Parvoviridae, Picornaviridae, and Reoviridae) compared to four in the pooled diarrhoeic samples (Anelloviridae, Circoviridae, Picornaviridae, and Reoviridae). It was not possible to associate a particular virus family with the investigated diarrhoea. In conclusion, this study does not support the hypothesis that the investigated diarrhoea was caused by known mammalian viruses. The results do, however, indicate that known mammalian viruses were present in the intestine as early as 24–48 hours after birth, indicating immediate infection post-partum or possibly transplacental infection.

MetLab : An In Silico Experimental Design, Simulation and Analysis Tool for Viral Metagenomics Studies

Metagenomics, the sequence characterization of all genomes within a sample, is widely used as a virus discovery tool as well as a tool to study viral diversity of animals. Metagenomics can be considered to have three main steps; sample collection and preparation, sequencing and finally bioinformatics. Bioinformatic analysis of metagenomic datasets is in itself a complex process, involving few standardized methodologies, thereby hampering comparison of metagenomics studies between research groups. In this publication the new bioinformatics framework MetLab is presented, aimed at providing scientists with an integrated tool for experimental design and analysis of viral metagenomes. MetLab provides support in designing the metagenomics experiment by estimating the sequencing depth needed for the complete coverage of a species. This is achieved by applying a methodology to calculate the probability of coverage using an adaptation of Stevens’ theorem. It also provides scientists with several pipelines aimed at simplifying the analysis of viral metagenomes, including; quality control, assembly and taxonomic binning. We also implement a tool for simulating metagenomics datasets from several sequencing platforms. The overall aim is to provide virologists with an easy to use tool for designing, simulating and analyzing viral metagenomes. The results presented here include a benchmark towards other existing software, with emphasis on detection of viruses as well as speed of applications. This is packaged, as comprehensive software, readily available for Linux and OSX users at https://github.com/norling/metlab.

Ultradeep Pyrosequencing and Molecular Modeling Identify Key Structural Features of Hepatitis B Virus RNase H, a Putative Target for Antiviral Intervention

ABSTRACT Last-generation nucleoside/nucleotide analogues are potent against hepatitis B virus (HBV) and have a high barrier to resistance. However, delayed responses have been observed in patients previously exposed to other drugs of the same class, long-term resistance is possible, and cure of infection cannot be achieved with these therapies, emphasizing the need for alternative therapeutic approaches. The HBV RNase H represents an interesting target because its enzyme activity is essential to the HBV life cycle. The goal of our study was to characterize the structure of the HBV RNase H by computing a 3-dimensional molecular model derived from E. coli RNase H and analyzing 2,326 sequences of all HBV genotypes available in public databases and 958,000 sequences generated by means of ultradeep pyrosequencing of sequences from a homogenous population of 73 treatment-naive patients infected with HBV genotype D. Our data revealed that (i) the putative 4th catalytic residue displays unexpected variability that could be explained by the overlap of the HBx gene and has no apparent impact on HBV replicative capacity and that (ii) the C-helix-containing basic protrusion, which is required to guide the RNA/DNA heteroduplex into the catalytic site, is highly conserved and bears unique structural properties that can be used to target HBV-specific RNase H inhibitors without cross-species activity. The model shows substantial differences from other known RNases H and paves the way for functional and structural studies as a prerequisite to the development of new inhibitors of the HBV cell cycle specifically targeting RNase H activity.

Viral metagenomics reveals the presence of highly divergent quaranjavirus in Rhipicephalus ticks from Mozambique

ABSTRACT Background: Ticks are primary vectors for many well-known disease-causing agents that affect human and animal populations globally such as tick-borne encephalitis, Crimean-Congo hemorrhagic fever and African swine fever. In this study, viral metagenomics was used to identify what viruses are present in Rhipicephalus spp. ticks collected in the Zambezi Valley of Mozambique. Methods: The RNA was amplified with sequence-independent single primer amplification (SISPA) and high-throughput sequencing was performed on the Ion Torrent platform. The generated sequences were subjected to quality check and classfied by BLAST. CodonCode aligner and SeqMan were used to assemble the sequences. Results: The majority of viral sequences showed closest sequence identity to the Orthomyxoviridae family, although viruses similar to the Parvoviridae and Coronaviridae were also identified. Nearly complete sequences of five orthomyxoviral segments (HA, NP, PB1, PB2, and PA) were obtained and these showed an amino acid identity of 32–52% to known quaranjaviruses. The sequences were most closely related to the Wellfleet Bay virus, detected and isolated from common eider during a mortality event in the USA. Conclusions: In summary, this study has identified a highly divergent virus with in the Orthomyxoviridae family associated with Rhipicephalus ticks from Mozambique. Further genetic and biological studies are needed in order to investigate potential pathogenesis of the identified orthomyxovirus.

Simulating Illumina metagenomic data with InSilicoSeq

Motivation The accurate in silico simulation of metagenomic datasets is of great importance for benchmarking bioinformatics tools as well as for experimental design. Users are dependant on large‐scale simulation to not only design experiments and new projects but also for accurate estimation of computational needs within a project. Unfortunately, most current read simulators are either not suited for metagenomics, out of date or relatively poorly documented. In this article, we describe InSilicoSeq, a software package to simulate metagenomic Illumina sequencing data. InsilicoSeq has a simple command‐line interface and extensive documentation. Results InSilicoSeq is implemented in Python and capable of simulating realistic Illumina (meta) genomic data in a parallel fashion with sensible default parameters. Availability and implementation Source code and documentation are available under the MIT license at https://github.com/HadrienG/InSilicoSeq and https://insilicoseq.readthedocs.io/. Supplementary information Supplementary data are available at Bioinformatics online.